NDLI: New Model for Residual Value Prediction of the Used Car Based on BP Neural Network and Nonlinear Curve Fit

Content Provider	IEEE Xplore Digital Library
Author	Shen Gongqi Wang Yansong Zhu Qiang
Copyright Year	2011
Abstract	A new model for predicting the residual value of the private used car with various conditions, such as manufacturer, mileage, time of life, etc., was developed in this paper. A comprehensive method combined by the BP neural network and nonlinear curve fit was introduced for optimizing the model due to its flexible nonlinearity. Firstly, some distribution curves of residual value of the used cars were analyzed in time domain. Then, the BP neural network (NN) was established and used to extract the feature of the distribution curves in various conditions. A set of schemed data was used to train the NN and reached the training goal. Finally, the schemed data as inputs and the NN outputs were organized for nonlinear curve fit. Conclusion was drawn that the newly proposed model is feasible and accurate for residual value prediction of the used cars with various conditions.
Starting Page	682
Ending Page	685
File Size	290362
Page Count	4
File Format	PDF
ISBN	9781424490103
DOI	10.1109/ICMTMA.2011.455
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-01-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training nonlinear curve fit used car BP neural network Biological system modeling Artificial neural networks Predictive models Maintenance engineering Feature extraction Appraisal
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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